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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Evaluating Awkward Arrays, uproot, and coffea as a query platform for High Energy Physics Data

Query languages for High Energy Physics (HEP) are an ever present topic within the field. A query language that can efficiently represent the nested data structures that encode the statistical and physical meaning of HEP data will help analysts by ensuring their code is more clear and pertinent. As the result of a multi-year effort to develop an in-memory columnar representation of high energy physics data, the NumPy, Awkward Array, and uproot Python packages present a mature and efficient interface to HEP data. Atop that base, the coffea package adds functionality to launch queries at scale, manage and apply experiment-specific transformations to data, and present a rich object-oriented columnar data representation to the analyst. Recently, a set of Analysis Description Language (ADL) benchmarks has been established to compare HEP queries in multiple languages and frameworks. In this paper we present these benchmark queries implemented within the coffea framework and discuss their readability and performance characteristics. We find that the columnar queries perform as well or better than the implementations given in previous studies.

Gray, L.↗
DOE OSTI2024

High-Temperature Wireless Sensor Platform Powered by Energy Scavenging

This paper reports on the development of key components required for a self-powered oscillator unit designed to wirelessly transmit its signal under full insertion in high-temperature (HT) harsh-environments (HE), such as those present in power plants and industrial settings (metallurgic, oil extraction, molding, and aerospace). The oscillator employed a silicon carbide (SiC) power transistor and HT passive components on a screen-printed alumina circuit board capable of operation beyond 300 °C. The HT oscillator circuit was powered solely by in-situ energy scavenging thermoelectric generator (TEG) modules using passive cooling, eliminating the need for an external power supply or active cooling. In addition, a silicon-based external booster circuit was used to achieve the required TEG voltage regulation to test the TEG-powered HT oscillator circuit. The TEG-powered oscillator circuit was tested inside a non-metallic furnace from room temperature to over 300 °C for transmission of a wireless signal, which was detected outside the furnace at 11 ft (3.4 m). Such a wireless transmitting system powered only by in-situ TEGs, with no requirement for external power or active cooling, is very attractive for flexible, mobile stand-alone control and sensor units targeted for operation in HT HE conditions found in power plants and industrial settings.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2021

Predictive Data-driven Platform for Subsurface Energy Production

Subsurface energy activities such as unconventional resource recovery, enhanced geothermal energy systems, and geologic carbon storage require fast and reliable methods to account for complex, multiphysical processes in heterogeneous fractured and porous media. Although reservoir simulation is considered the industry standard for simulating these subsurface systems with injection and/or extraction operations, reservoir simulation requires spatio-temporal “Big Data” into the simulation model, which is typically a major challenge during model development and computational phase. In this work, we developed and applied various deep neural network-based approaches to (1) process multiscale image segmentation, (2) generate ensemble members of drainage networks, flow channels, and porous media using deep convolutional generative adversarial network, (3) construct multiple hybrid neural networks such as convolutional LSTM and convolutional neural network-LSTM to develop fast and accurate reduced order models for shale gas extraction, and (4) physics-informed neural network and deep Q-learning for flow and energy production. We hypothesized that physicsbased machine learning/deep learning can overcome the shortcomings of traditional machine learning methods where data-driven models have faltered beyond the data and physical conditions used for training and validation. We improved and developed novel approaches to demonstrate that physics-based ML can allow us to incorporate physical constraints (e.g., scientific domain knowledge) into ML framework. Outcomes of this project will be readily applicable for many energy and national security problems that are particularly defined by multiscale features and network systems.

58 GEOSCIENCES↗
DOE OSTI2024

Survey of Use Cases and Scenarios on the Open Energy Data Initiative Solar Systems Integration (OEDI SI) Platform

The Open Energy Data Initiative Solar Systems Integration (OEDI SI) Data and Modeling Platform offers a comprehensive set of use cases tailored for power systems analysis. Each use case is centered around a specific power system analysis problem, supported by composite input data and reference algorithms. These composite input datasets are meticulously assembled using OEDI SI's data preprocessing tools, which integrate raw data from various sources. The primary objectives of the OEDI SI Platform include facilitating access to composite input data through widely accepted input/output formats and verified results. This accessibility enables power system network researchers and developers to validate their algorithms and showcase their applications' capabilities to the broader community. Moreover, the platform strives to promote reproducible, robust, replicable, and generalizable solar systems integration research.

14 SOLAR ENERGY↗
DOE OSTI2025

Fossil Energy in the Hydrogen Economy – A Carbon-Water-Energy Nexus Adaptive Evaluation Platform

This project develops tools to evaluate fossil energy within the hydrogen economy. In particular, the project seeks to explore the Carbon-Water-Energy Nexus and develop adaptive evaluation tools. The primary goal of this project was to evaluate fossil-based hydrogen production methods with an emphasis on their sustainability, particularly with respect to carbon emissions and water use. The overall technical objectives that guided this evaluation consisted of 1) technology assessment, which sought to establish a comprehensive baseline of existing and emerging technologies for the generation, transportation, storage, and end use of hydrogen derived from fossil fuels, 2) carbon footprint analysis through quantification and analysis of carbon emissions associated with these hydrogen technologies, and identification of novel strategies and technologies that can effectively mitigate the carbon footprint, 3) water intensity assessment by evaluating the water needs (water-energy nexus) associated with different fossil fuel-based hydrogen technologies and proposing strategies to reduce water use, thus ensuring sustainable resource management, and 4) review of regulatory, policy and economic trends were examined to provide an overview of the factors influencing the adoption and integration of fossil fuel-derived hydrogen technologies into current energy markets. Beyond the technical outcomes, this project contributed to 5) education and workforce development through targeted training and educational opportunities for engineering students, preparing the next generation of professionals with technical, economic, and regulatory expertise in the hydrogen economy. Ultimately, this effort was intended to train the future workforce to provide useful insights to policymakers, industry stakeholders, and the broader energy community to facilitate informed decisions and responsible development within the hydrogen economy.

08 HYDROGEN↗
DOE OSTI2022

Livewire Data Platform-A Solution for Energy Efficient Mobility Systems (EEMS) Data Sharing

This presentation is an overview of progress made on the Livewire Data Platform since June 2021. Livewire is a publicly accessible platform for sharing energy efficiency and mobility research data funded by DOE's Vehicle Technologies Office. Core services and platform capabilities of Livewire include: Free, secure data storage; Access management that allows data owners to control who sees their data; Data collection and preservation; Quality characterization; Detailed access and download metrics; and Increased visibility of projects and data.

energy efficiency mobility↗
DOE OSTI2023

Livewire Data Platform-A Solution for Energy Efficient Mobility Systems (EEMS) Data Sharing

This presentation is an overview of progress made on the Livewire Data Platform since June 2022. Livewire is a publicly accessible platform for sharing energy efficiency and mobility research data funded by DOE's Vehicle Technologies Office. Core services and platform capabilities of Livewire include: Free, secure data storage; Access management that allows data owners to control who sees their data; Data collection and preservation; Quality characterization; Detailed access and download metrics; and Increased visibility of projects and data. Anyone can create an account and access data at https://livewire.energy.gov/.

energy efficiency↗
DOE OSTI2020

Livewire Data Platform - A Solution for Energy Efficient Mobility Systems (EEMS) Data Sharing

The Livewire Data Platform is a data storage and exchange platform. It provides: a platform, allowing data sharing and discovery by linking disparate data sources to a single website via application programming interfaces (APIs); a community, building partnerships and collaboration rather than competition; a system, allowing shared data to increase in size and complexity as EEMS evolves.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Automated Mobility Platforms (AMPs) for Versatile, Energy Efficient, Facility and District Scale Transport

The Automated Mobility Platforms (AMPs) concept is envisioned as an on-demand network of automated lightweight electric vehicles serving mobility needs in a large facility or district-scale setting. Supplanting the function of legacy automated people mover systems, AMPs is scalable to meet the needs of moving people in large interior spaces with destinations that are too distant for walking and in which larger motor vehicles would be unfeasible or undesirable. The AMPs system is designed for automated management and operation, extending to how and where the vehicles are sent to serve mobility needs, as organized through a supervisory management system. AMPs vehicles are requested by users via smartphone app or buttons located on interactive infrastructure elements. AMPs vehicles function similarly to elevators, though in the horizontal plane, wherein users summon vehicles, and are moved point-to-point, with user requested destinations set through intuitive interfaces. The concept targets extensibility, manageability, and performance improvements over legacy technologies, with accessibility and safety features integrally designed into the system.

ADA supportive modes↗
DOE OSTI2022

Intersections of Disadvantaged Communities and Renewable Energy Potential: Data Set and Analysis to Inform Equitable Investment Prioritization in the United States

Renewable energy development can bolster local economies through job creation, local tax revenues, and reduced energy costs; however, communities most in need of economic development and employment opportunities often see lower levels of renewable energy deployment. We sought to identify areas where disadvantaged community indicators and high generation potential from cost-effective renewable energy opportunities intersect and deployment could lead to economic development and job creation. This presentation will highlight several of our findings. This research and the associated county-level data set are intended to inform national- and state-level energy-related assistance programs, economic development efforts, and infrastructure programs seeking to prioritize investments in disadvantaged communities.

community energy planning↗
DOE OSTI2024

Advances in building data management for building performance standards using the SEED platform

Reducing energy consumption and greenhouse gas emissions in the built environment is a critical step in achieving emission goals to mitigate climate change impacts. Local, federal, and international jurisdictions are deploying several methods to reduce energy and emissions such as voluntary and mandatory benchmarking and building performance standards, requiring building owners to reach energy and emission targets. Jurisdictions leveraging benchmarking and building performance standards require knowledge of the buildings covered; which is a large task due to staffing constraints, limited information on building characteristics and tax parcel data, and the need for advanced data management techniques to align datasets. This paper describes an open-source platform's recent advances to create consistent taxonomies, identify erroneous data, enable auditability, and track building performance. The paper concludes with two use cases on how the platform has been used by jurisdictions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Local Power: Comparing County-Level Renewable Energy Potential to Consumption Using the SLOPE Platform

Wide-scale deployment of renewable energy technologies has the potential to significantly reduce greenhouse gas emissions and mitigate the effects of climate change. Many communities have ambitious clean energy goals with targets for locally generated renewable energy. To inform state and local clean energy planning, analysts from the Joint Institute for Strategic Energy Analysis (JISEA) and National Renewable Energy Laboratory (NREL) used data from NREL's State and Local Planning for Energy (SLOPE) platform to compare annual technical generation potential of renewable energy technologies to modeled electricity consumption in every county of the contiguous United States. Annual costs were calculated to produce a 20% share of electricity consumed annually from each technology to examine localized cost effectiveness of a diversified mix of generation sources. For example, combining distributed and utility-scale wind and solar generation can offset the need for storage and nonintermittent fossil resources to achieve high deployment of renewables. This county-level analysis provides insight into where localized renewable energy generation could cost-effectively match annual electricity consumption.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

New Energy Planning Tools from NREL

This is a very brief description of the State and Local Planning for Energy (SLOPE) platform and State and Local Energy Profiles datasets to be included in the Tools issue of the Colorado chapter of the American Planning Association newsletter.

48 EE - Weatherization and Intergovernmental Progr↗